Prepare a report analyzing land use and housing outcomes in one County (of your choice) in the Bay Area. You are welcome to include as many data-driven insights as you’d like, with the many kinds of housing and parcel datasets available from the Census Bureau and elsewhere, but at the minimum, you must include:

  1. Using techniques from Section 6.1, an analysis of housing burden for a specific sub-population of your choice (e.g. renters vs. owners, race or ethnicity, households with children). Using a burden threshold of 30% (or another of your choice), estimate the total annual funding that would be required to eliminate this kind of housing burden for your population. Include a map visualizing where this housing-burden sub-population lives in your County.

First I performed an analysis of housing burden on the two sub-populations of owners and renters. I calculated the fraction of owners and renters that experience housing burden, with a threshold of 30%, within San Francisco County specifically. I have also included maps of owner and renter housing burden across San Francisco County.

## [1] "Proportion of owners paying more than 30% of their income on housing"
## [1] 0.1071335
## [1] "Proportion of renters paying more than 30% of their income on housing"
## [1] 0.2263645

Next I broke up the owner sub-population into three sub-sub-populations based on race and ethnicity: one for white owners, one for Black owners, and one for Hispanic/Latino owners. I performed an analysis of housing burden on these sub-sub-populations. I calculated the fraction of these groups of owners that experience housing burden, with a threshold of 30%, within San Francisco County specifically. I have also included maps of each of these owner group’s housing burden across San Francisco County. I found that 8.56% of white owners, 9.16% of Black owners, and 7.8% of Hispanic/Latino owners experience housing burden.

I did the same for the renter sub-population, finding that 20.74% of white renters, 39.34% of Black renters, and 33.83% of Hispanic/Latino renters experience housing burden.

## [1] "Proportion of owners paying more than 30% of their income on housing"
## [1] 0.1071335
## [1] "Proportion of white owners paying more than 30% of their income on housing"
## [1] 0.08562461
## [1] "Proportion of Black owners paying more than 30% of their income on housing"
## [1] 0.09164389
## [1] "Proportion of Hispanic/Latino owners paying more than 30% of their income on housing"
## [1] 0.07786199
## [1] "Proportion of renters paying more than 30% of their income on housing"
## [1] 0.2263645
## [1] "Proportion of white renters paying more than 30% of their income on housing"
## [1] 0.2074027
## [1] "Proportion of Black renters paying more than 30% of their income on housing"
## [1] 0.3934407
## [1] "Proportion of Hispanic/Latino renters paying more than 30% of their income on housing"
## [1] 0.3382529

Below are the maps of owner housing burden overall, as well as white, Black, and Hispanic/Latino owner housing burden, respectively.

Below are the maps of renter housing burden overall, as well as white, Black, and Hispanic/Latino renter housing burden, respectively.

  1. For some location in San Francisco (i.e. one census block group’s worth of parcels, or, using techniques from Chapter 5, parcels within 5 minutes walking from a transit station), an analysis of the distribution of property uses, compared to what can be built under existing zoning, or what could be built under zoning reform through recent legislation like SB50. At the minimum, calculate “unused dwelling units” as was done in Section 6.2 for your study area.

I have calculated and visualized the unused dwelling units for three census tracts in the Mission District in San Francisco. The tracts are: 020800, 020900, and 022803.

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